Submission 3 - Final¶

Instructions

  • Fill out the 'Basic Information','Complex Hypotheses - Findings / Insights', 'Black vs White Hat Visualization' sections (replace the TODOs with your information)
    • If your visualization is interactive, create a short video that shows the interactivity (max. 3 min).
  • Export the Jupyter notebook as a HTML file and save it in this repository.
    • Go to 'File' -> 'Save and Export Notebook As..' -> 'HTML'.
    • Save it locally in your project folder. You can leave the name as it is.
    • If you have a video, then add it to the project folder.
    • Push your local changes to the GitHub repository.
  • Make sure all your files are up-to-date (pushed) in the Github repository.
    • Check if all Jupyter notebooks are executeable, theses will be the backup if there were problems with the HTML file submissions.
    • We will collect the protect via GitHub Classroom.

Basic Information¶

Team Name: The Fantastic Four

Team Members:

  • Ivan Drinovac - k12104744
  • Mohamed Abdelaziz - k12137202

Dataset Description:
(max. 75 words)

Historical Data of various causes of deaths across different countries along the timeline from 1990 up until 2019, Combined with The Population by country to derive more insight into the data.


Complex Hypotheses - Findings / Insights¶

Instructions:

  • Add your visualizations (max. 4) here
    • The visualizations should show the findings / insights
  • Add the descriptions for all your findings / insights (max. 150 words)
    • The description should also relate to the visualizations above.

Visualizations¶

In [1]:
import pandas as pd
import utils

df = pd.read_csv('../data/cause_of_deaths_cont_pop.csv')
In [ ]:
utils.plot_hyp_3_1(df)
In [ ]:
utils.plot_hyp_3_2(df)
In [ ]:
utils.plot_hyp_4_1(df)

Description¶

The first graph, was used to identify the countries that suffered the highest number of fatalities due to Conflict and War, summed-up over the past 30 years; That contributed to selecting the top 7 countries in order to study the trends of the drug-abuse, alcohol-abuse and self-harm mortalities after these periods of conflict that was expressed in the next graph which showed the existence of an up-trend in some of the selected countries, but contradiction in others, which doesnot confirm or refute the hypothesis.

In the third graph, the Percentage of fatalities due to the Maternal Disorders, Neonatal Disorders, Tuberclosis and Malaria Diseases, showed an overall down trend over the years which can mean better health conditions around the globe, and a correlation between the variables can be concluded.


Black vs White Hat Visualization¶

Black Hat Visualization¶

Instructions:

  • Add your black hat visualization
  • Add a description explaining your motivation and design process in producing this visualization (max. 150 words)

Visualization¶

In [ ]:
utils.plot_black(df)

Description¶

The idea behind the graph is to fool the reader into thinking that the more you eat healthy diet affects the chance that you get alzheimer disease, by normalizing the data and reversing one of the variables, and we also tried to increase its credibility of the graph to the reader by adding a famous sponsor to the title, which goes against the best practices.

White Hat Visualization¶

Instructions:

  • Add your white hat visualization
  • Add a description explaining your motivation and design process in producing this visualization (max. 150 words)

Visualization¶

In [ ]:
utils.plot_white(df)

Description¶

The graph shows the number of deaths due to nutrition deficiencies and alzheimer diseases over the span of 30 years from 1990 to 2019, which shows a negative correlation between the variables, as we chose a line graph to ease the readability of the graph between the 2 diseases over time.